Screening and identification of cucumber germplasm and rootstock resistance against the root-knot nematode (Meloidogyne incognita)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Root-knot nematodes (Meloidogyne spp) are destructive agricultural pests that reduce the productivity of cultivated vegetables worldwide, especially when vegetables are cropped continuously in greenhouses. Cucumbers (Cucumis sativus L.), in particular, suffer extensive damage due to root-knot nematodes, and only a few wild species are known to be resistant. Grafting of cultivated plants to rootstocks of known resistant germplasms could be an effective method to resolve this problem. In this study, 21 cucumber germplasms and seven rootstocks were evaluated for resistance based on the growth of cucumber seedlings and resistance indexes to Meloidogyne incognita, which were surveyed 25 days after inoculation with M. incognita. Cluster analysis and principal component analysis (PCA) were used to investigate the resistance of 21 cucumber germplasms and seven rootstocks based on their growth and resistance indexes after inoculation with M. incognita. These analyses showed that the 21 germplasms and seven rootstocks could be divided into three groups based upon their resistance levels: moderately resistant, susceptible, and highly susceptible to M. incognita. All 21 cucumber germplasms exhibited susceptibility or high susceptibility to M. incognita and most rootstocks exhibited moderate resistance. The PCA results were consistent with those of the clustering analysis. The Jinyou No.1 cultivar had the highest resistance to M. incognita among the 21 cucumber germplasms, and Huangzhen No.1 cultivar had the highest resistance among the seven rootstock cultivars.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it